p. 89
–97
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The QRD LS algorithm is generally recognised for its superior numerical properties under finite-precision implementation. Furthermore, its systolic architecture is well suited for VLSI implementation. In DFE applications the inherent and implementation nonlinearities make it impossible to analyse precisely all effects of finite-precision arithmetic. The paper presents finite precision results of a QRD LS DFE using the TMS320C25 16-bit precision DSP processors as a simulation platform. Using the bit error rate as a performance measure, results are presented for 2-PSK, 4-PSK and Pi/4-DQPSK modulation formats. Also presented are the numerical accuracy and convergence sensitivity for the filter weights. These results may serve as a basis for practical implementation of QRD LS DFEs.

p. 98
–102
(5)
An explicit form for the Slepian model of Gaussian noise X(t + τ) conditioned on the value X(t) and any desired number N of its derivatives X'(t), X"(t), …, X(N)(t) at a given time t is obtained by using determinants for the Gram- Schmidt orthogonalisation of linear combinations of random variables, and then applying them to the least-mean-squared-error estimation of any zero-mean stationary random process. In this way a number of widely useful results are unified, clarified, simplified and extended. Finally, the application to a random process with a spectral density of Gaussian shape is studied.

p. 107
–113
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An algorithm, the bootstrap filter, is proposed for implementing recursive Bayesian filters. The required density of the state vector is represented as a set of random samples, which are updated and propagated by the algorithm. The method is not restricted by assumptions of linearity or Gaussian noise: it may be applied to any state transition or measurement model. A simulation example of the bearings only tracking problem is presented. This simulation includes schemes for improving the efficiency of the basic algorithm. For this example, the performance of the bootstrap filter is greatly superior to the standard extended Kalman filter.

p. 114
–122
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For the passive estimation of directions of arrivals (DOAs) of transmitting sources from an antenna array, high resolution estimators can be achieved from maximum likelihood or signal subspace based concepts, provided that certain model assumptions are satisfied. For the signal subspace class of methods, the sources are nearly always regarded as being stationary during the observation interval of the array data. If this is the case, and if all the other model assumptions are valid, then the DOA can be estimated to arbitrary accuracy in the presence of noise by observing the data over a sufficiently long time interval. When sources are in fact moving relative to the receiving array, errors are induced in signal subspace methods. These depend on the extent of the source motion. Hence there is a trade-off between decreasing noise errors and increasing motion errors as the observation time is increased, and some optimum observation period exists. In some cases, however, even the performance at the optimum observation interval may be unsatisfactory, and alternative approaches are desirable. Signal subspace concepts break down when sources are moving, and maximum likelihood methods for moving sources are computationally expensive. To overcome these problems three novel algorithms have been developed for the joint estimation of source position and velocity from a batch of array data for sources moving with constant angular velocity. These allow increased accuracy in the source position determination, and provide unbiased velocity estimates. The performance of the estimators is compared to the Cramer-Rao lower bound.

p. 129
–137
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Modulation of the radar pulse repetition interval (PRI) is a conventional technique to improve the target velocity coverage in a moving target indicator (MTI) filter. Typically, a given pattern of interpulse intervals is periodically repeated (staggered PRI). Additionally, the staggered PRI gives us some protection against PRI analysis in an electronic intelligence environment. Nevertheless, this protection is limited by the repetitive character of the PRI modulation pattern. Much greater protection can be achieved by means of a random selection of the PRI between fixed bounds.This paper presents an analysis of the digital MTI for two types of PRI random generation. In the first type, small deviations with respect to a mean PRI are randomly generated (random deviation method, RDM). In the second type, the intervals themselves are randomly selected random interval method, RIM). We derive for both cases the relationship between the velocitydependent gain factor and the probability density function (PDF) of the corresponding random variables. This allows us to predict the influence of the PDF in the expected performance. Specific design strategies that take into account practical constraints, like the maximum unambiguous range and the dwell time, are also proposed for each method.

p. 138
–144
(7)
This paper investigates the existence and treatment of systematic errors in geometric height measurement systems. A minimal system of one SSR aided by a low power omni radar equipped with an independent interrogator is taken for reference. Biases are identified to be created by the aircraft transponder and by the nonlinear processing of the available noisy radar range and bearing measurements. The first source is treated by augmenting the estimation process to include the transponder bias. The latter source creates an ‘inherent bias’ which cannot be estimated by augmenting the estimation process. The inherent bias is further analysed by determining the main factors affecting its magnitude. It is shown that the inherent bias limits the useful area in which the geometric height can be reliably estimated. Although the inherent bias investigation method is primarily derived for the SSR-omni measurement system, it can be applied in a straightforward manner to other geometric height monitoring systems employing nonlinear processing of the original measurements.

p. 145
–152
(8)
Hardware and software aspects of the design of a microprocessor-based radionavigation receiver are discussed. The receiver uses the orange channel of the Decca Navigator transmissions, and is based on a design published by J.D. Last. Unlike Last's design, it computes a position fix by directly measuring the phase of the signal, using phase-locked-loop techniques, with software correction for interrupt latency. A phasedetermination algorithm is presented which compensates for local oscillator drift and for skew error due to movement of the vehicle during the measurement cycle, and which appears to be particularly resistant to errors due to skywave propagation effects. A further algorithm, based on number-theoretic techniques, is presented for performing zone identification by phase comparison using the master (6f) and orange (8.2f) transmissions only.